Survival of breast cancer patients following surgery: a detailed assessment of the multi-layer perceptron and Cox´s proportional hazard model

Author

Lisboa, Paulo J G ; Wong, Helen ; Vellido, Alfredo ; Kirby, Simon P J ; Harris, Peter ; Swindeil, R.

Author_Institution

Sch. of Comput. & Math., Liverpool John Moores Univ., UK

Volume

1

fYear

1998

fDate

4-8 May 1998

Firstpage

112

Abstract

The prognostic assessment of breast cancer patients following surgery to excise the tumour and other pathological tissue, is an important consideration in determining the most appropriate course of adjuvant therapy for the patient. The paper compares the relative predictive performance of a neural network and an established statistical method, on the basis of their ROC and Kaplan-Meier curves, using information available at the time of surgery

Keywords

medical computing; multilayer perceptrons; patient treatment; statistical analysis; surgery; Cox´s proportional hazard model; Kaplan-Meier curves; ROC; breast cancer patients; multi-layer perceptron; prognostic assessment; relative predictive performance; surgery; therapy; Breast cancer; Databases; Europe; Hazards; Hospitals; Input variables; Multilayer perceptrons; Oncological surgery; Pathology; Tumors;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7576

Print_ISBN

0-7803-4859-1

Type

conf

DOI

10.1109/IJCNN.1998.682246

Filename

682246